Welcome to the Xilinx Embedded Vision Portal
Xilinx programmable logic devices (called Field Programmable Gate Arrays, or FPGAs) are the product of choice for the design of tens of thousands of products that improve the quality of our everyday lives. Due to their inherent flexibility, Xilinx award-winning programmable logic devices enable more than 20,000 customers to deliver innovative new products to market in a matter of weeks while drastically reducing their research and development costs.
Embedded Vision (EV) has become an essential, if not differentiating system requirement for the vast array of applications and markets we serve. Industries such as Aerospace, Automotive, Broadcast, Defense, Industrial and Medical, to name a few, require the inherent flexibility of our FPGAs to hasten their delivery of new EV-capable applications implemented with the latest standards, functions and algorithms and to quickly scale, migrate and differentiate those products over time.
To better serve the needs of so varied a customer base, Xilinx products are delivered as programmable platforms that provide easy access and efficient use of our devices by surrounding them with an integrated set of design tools, intellectual property (IP) cores, boards and reference designs that target the needs of the designer, the domain (embedded, DSP, connectivity) and the market in which the device will be used.
Free Embedded Vision Training
Here are our latest training offerings; for a complete list, go to our Embedded Vision Training page.
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May 17, 2013 José Alvarez, Engineering Director for Video Technology at Xilinx, presents the "Challenges and Opportunities in Accelerating OpenCV" tutorial within the "Developing Vision Software, Accelerators and Systems" technical session at the April 2013 Embedded Vision Summit. Computer vision continues to see increased adoption across a wide variety of applications. The industry's trend towards the incorporation of Smarter Vision capabilities is driving the need for ever more intelligent algorithms that are capable of image understanding. |
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April 08, 2013 Semiconductor and software advances are enabling medical devices to derive meaning from digital still and video images. By Brian Dipert |
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March 18, 2013 By Tom Catalino |
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March 07, 2013 By Jon Alexander, Technical Marketing Manager for ISM (Industrial, Scientific, Medical) Markets |
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October 18, 2012 Dan Isaacs, Director of Processing Product Marketing at Xilinx, and Michael Fawcett, Chief Technology Officer at iVeia, presents the "Image Processing for Object Recognition and Tracking" tutorial, part of the "Embedded Vision Applications and Algorithms" technical session at the September 2012 Embedded Vision Summit. Topics discussed included trends in image processing for embedded vision applications, and object recognition leveraging OpenCV with a Canny edge-detect case study. |
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April 20, 2012 By Sateesh Reddy Jonnalagada and Vamsi Krishna |
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March 23, 2012 Rapidly emerging applications in the area of embedded vision require ability to do real-time processing of one or more streams of HD video at high frame rates. In this demonstration, Xilinx's Navanee Sundaramoorthy, Product Manager for Processing Platforms, shows how you can use the Zynq-7000 Extensible Processing Platform with dual ARM Cortex-A9 processors and programmable logic for such applications. The programmable logic in the Zynq Z7020 brings 1080p60 video in and out of the device, as well as doing high data rate video processing. |
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March 20, 2012 Converting images from one color domain to another is a common and often misunderstood operation in embedded vision processing. Image formats and color spaces vary when information is interchanged among processing domains. FPGAs provide a flexible, fast and scalable way of converting images using readily available IP cores. This video tutorial from José Alvarez, Video Technology Engineering Director at Xilinx Corporation, provides a quick reference to the available IP to perform this task efficiently and conveniently. |
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February 28, 2012 By José Alvarez |
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January 31, 2012 By Brian Dipert |
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